Skip to content

Advertisement

Genetics Selection Evolution

What do you think about BMC? Take part in

Aims and scope

Genetics Selection Evolution is an open access, peer-reviewed, online journal dedicated to original research on all aspects of genetics and selection in domestic animal species and other species providing results of immediate interest for farm animals' genetics.

Featured Picture

Featured: Simultaneous fitting of genomic-BLUP and Bayes-C components in a genomic prediction model

Iheshiulor et al. develop a novel iterative approach to genome prediction that combines linear and non-linear methods.

Articles

View all articles
View all articles

Editors-in-Chief

Didier Boichard, INRA, France
Jack Dekkers, Iowa State University, US
Helene Hayes, INRA, France
Julius van der Werf, University of New England, Australia

Featured collection: ISAFG 2015

This special issue contains articles published in collaboration with the 6th International Symposium on Animal Functional Genomics, held in Piacenza, Italy, 27th-29th July 2015.

Andrea Doeschel Wilson

GSE welcomes the newest Associate Editor

Andrea Doeschl-Wilson leads a research group at the Roslin Institute (University of Edinburgh, UK) on mathematical modelling and statistical inference of infectious diseases and other dynamic processes in livestock, with particular focus on dissecting the role of host genetics on these processes.
Her research combines methods from mathematical dynamical systems theory and quantitative genetics to understand and predict the influence of genetic effects on the health and performance of individual animals and livestock populations.

About the Editors-in-Chief

D Boichard

Didier Boichard

Didier Boichard is currently leading the Cattle Genetics and Genomics research group in the laboratory of Animal Genetics and Integrative Biology at INRA (French National Institute for Agricultural Research) in Jouy-en-Josas.

His research is focused on dairy cattle genetics and breeding, particularly on the analysis of genetic variability of production and functional traits. He has managed the French national genetic evaluation for dairy cattle, sheep and goats and conducted projects for QTL detection and fine mapping. In 2002, in close collaboration with the French breeding industry, he implemented a large-scale marker-assisted selection programme, which has become a genomic selection programme since 2008.

j dekkers

Jack Dekkers

Jack Dekkers is professor and leader of the Animal Breeding and Genetics Section in the Department of Animal Science at Iowa State University (USA).

 His areas of research are quantitative genetics and animal breeding with application to swine and poultry genetics, including the use of molecular genetic and genomic information, QTL detection, marker-assisted and genomic selection, design, optimization and economic aspects of breeding strategies, and genetic aspects of residual feed intake in pigs.

h hayes

Helene Hayes

Helene Hayes is a researcher in the laboratory of Animal Genetics and Integrative Biology at INRA (French National Institute for Agricultural Research) in Jouy-en-Josas.

Her main focus is animal cytogenetics with a special interest on cattle, goat, sheep and rabbit cytogenetic maps and comparative mapping. Since 2005, she dedicates half her time to the management of the journal Genetics Selection Evolution.

j van der werf

Julius Van Der Werf

Professor Julius van der Werf holds a PhD (1990) in Animal Breeding from Wageningen University in the Netherlands. He moved to the University of New England (Armidale, Australia) in 1997, where he is now Professor in Animal Breeding and Genetics and Program Leader of Genetics in the Cooperative Research Center for Sheep Industry Innovation.

His research interests range from methodological issues on the estimation of genetic parameters (design and data structure, mixed models analysis, genetic evaluation models, random regression models) and genomic analysis (genomic prediction, genome wide association studies, design of experiments, models for genomic prediction, phasing and imputation) to applications for the optimization of animal breeding programs (breeding objectives, optimizing selection, optimizing, measurement, long and short term gains, genetic gain and genetic diversity, total genetic resource management).

Advertisement